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Research On The Risk Influencing Factors And Controlling Of Rural Online Credit Platforms In My Country

Posted on:2019-04-09Degree:MasterType:Thesis
Country:ChinaCandidate:D PeiFull Text:PDF
GTID:2439330548978284Subject:Finance
Abstract/Summary:
The continuous development of Internet technology has brought more deep integration of network and finance to bring the innovation of financial model,the most typical of which is Peer-to-peer network lending.As a new investment and financing mode,Peer-to-peer has filled the gap of traditional financial institutions and provided a new channel to some extent.In recent years,the state to help the three farmers continue to introduce new policies,but also make Peer-to-peer network loans to support the number of agricultural platforms increasing.However,China’s Peer-to-peer network loans to help the agricultural model started late,the development time is short,so most peer-to-peer platform does not have the ability to control risk,and then cause various problems,making network fraud,platform default and run away from the phenomenon often occurs.Based on this situation,this paper analyzes the factors that cause the risk of rural network credit in our country,and supplements the risk of rural net loan in China.Based on the existing domestic and foreign literatures on the research of rural network credit risk,this paper studies the credit risk of rural network in China by reference to other research on credit risk and loan risk.Through the study of a large number of literatures,it is found that the default risk is the most common risk in the network credit risk,so this paper focuses on the default risk and will be the main research object of the peasant household.Select the September 2017-February 2018 to help rural network loan platform-wing Dragon loans to participate in the 500-wing farmers plan,using the 5C factor analysis method to 500 farmers into character(borrower characteristics),capital(asset strength),Capacity(repayment capacity),Collateral(repayment guarantee)and claims(creditor’s rights)of these five categories,each major class is divided into different factors,at the same time,using descriptive statistics method and Logit regression analysis method,each factor is set as the independent variable,whether overdue repayment as the dependent variable,the influence degree of each risk factor on the default risk is analyzed,determine the key factors that affect the risk of default,and put forward the corresponding risk control measures.
Keywords/Search Tags:Rural network credit, risk, risk control, descriptive statistical, analysis logit regression analysis
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